ohs-foundation/fhir-data-pipes
ohs-foundation/fhir-data-pipes has 228 GitHub stars and 126 forks. Star changes are not measured yet. Last checked 2026-11-14 09:11 UTC. Last push 2026-11-10.
Measured star growth
- in 24h
- Collecting history
- in 7 days
- Collecting history
- in 15 days
- Collecting history
- in 1 month
- Collecting history
Net star changes over overlapping periods, not daily totals. Missing measurements are left blank. Stars measure attention, not software quality.
About
A collection of tools for extracting FHIR resources and analytics services on top of that data.
DataREADME.md
OriginalWhat is this?
This repository includes pipelines to transform data from a FHIR server (like HAPI, GCP FHIR store, or even OpenMRS) using the FHIR format into a data warehouse based on Apache Parquet files, or another FHIR server. There is also a query library in Python to make working with FHIR-based data warehouses simpler.
These tools are intended to be generic and eventually work with any FHIR-based data source and data warehouse. Here is the list of main directories with a brief description of their content:
pipelines/ *START HERE*: Batch pipelines to transform data from a FHIR-based source to an analytics-friendly data warehouse or another FHIR store.
docker/: Docker configurations for various servers/pipelines.
doc/: Documentation for project contributors. See the pipelines README and wiki for usage documentation.
utils/: Various artifacts for setting up an initial database, running pipelines, etc.
dwh/: Query library for working with distributed FHIR-based data warehouses.
bunsen/: A fork of a subset of the Bunsen project which is used to transform FHIR JSON resources to Avro records with SQL-on-FHIR schema.
e2e-tests/: Scripts for testing pipelines end-to-end.
NOTE: This was originally started as a collaboration between Google and the OpenMRS community.
Contributions
This is an open-source project and we welcome contributions. Our development process is also open. We use GitHub issues and review processes. If you are working on a feature or an issue, please comment on that GitHub issue to communicate with other developers. It would also be great to attend our weekly developers' calls on Tuesdays; here are the details:
- When: Tuesdays at 10 AM Eastern Time (Toronto)
- Where: Virtual at https://meet.google.com/ago-nmcc-oed
Explore related projects
Asabeneh/30-Days-Of-Python
The 30 Days of Python programming challenge is a step-by-step guide to learn the Python programming language in 30 days. This challenge may take more than 100 days. Follow your own pace. These videos may help too: https://www.youtube.com/channel/UC7PNRuno1rzYPb1xLa4yktw
78,725 starsgrafana/grafana
The open and composable observability and data visualization platform. Visualize metrics, logs, and traces from multiple sources like Prometheus, Loki, Elasticsearch, InfluxDB, Postgres and many more.
77,897 starsredis/redis
For developers, who are building real-time data-driven applications, Redis is the preferred, fastest, and most feature-rich cache, data structure server, and document and vector query engine.
77,491 starsapache/superset
Apache Superset is a Data Visualization and Data Exploration Platform
75,522 stars